Fluorescence-enhanced optical imaging on three-dimensional phantoms using a hand-held probe based frequency-domain intensified charge coupled device (ICCD) optical imager

Fluorescence-enhanced optical imaging is an emerging non-invasive and non-ionizing modality towards breast cancer diagnosis. Various optical imaging systems are currently available, although most of them are limited by bulky instrumentation, or their inability to flexibly image different tissue volumes and shapes. Hand-held based optical imaging systems are a recent development for its improved portability, but are currently limited only to surface mapping. Herein, a novel optical imager, consisting primarily of a hand-held probe and a gain-modulated intensified charge coupled device (ICCD) detector, is developed towards both surface and tomographic breast imaging. The unique features of this hand-held probe based optical imager are its ability to; (i) image large tissue areas (5×10 sq. cm) in a single scan, (ii) reduce overall imaging time using a unique measurement geometry, and (iii) perform tomographic imaging for tumor three-dimensional (3-D) localization. Frequency-domain based experimental phantom studies have been performed on slab geometries (650 ml) under different target depths (1-2.5 cm), target volumes (0.45, 0.23 and 0.10 cc), fluorescence absorption contrast ratios (1:0, 1000:1 to 5:1), and number of targets (up to 3), using Indocyanine Green (ICG) as fluorescence contrast agents. An approximate extended Kalman filter based inverse algorithm has been adapted towards 3-D tomographic reconstructions. Single fluorescence target(s) was reconstructed when located: (i) up to 2.5 cm deep (at 1:0 contrast ratio) and 1.5 cm deep (up to 10:1 contrast ratio) for 0.45 cc-target; and (ii) 1.5 cm deep for target as small as 0.10 cc at 1:0 contrast ratio. In the case of multiple targets, two targets as close as 0.7 cm were tomographically resolved when located 1.5 cm deep. It was observed that performing multi-projection (here dual) based tomographic imaging using a priori target information from surface images, improved the target depth recovery over using single projection based imaging. From a total of 98 experimental phantom studies, the sensitivity and specificity of the imager was estimated as 81-86% and 43-50%, respectively. With 3-D tomographic imaging successfully demonstrated for the first time using a hand-held based optical imager, the clinical translation of this technology is promising upon further experimental validation from in-vitro and in-vivo studies.

Design and implementation of a multisite data repository for pediatric epilepsy

This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.

In vivo biocompatibility evaluation of composite polymeric materials for use in a novel artificial heart valve

A novel trileaflet polymer valve is a composite design of a biostable polymer poly(styrene-isobutylene-styrene) (SIBS) with a reinforcement polyethylene terephthalate (PET) fabric. Surface roughness and hydrophilicity vary with fabrication methods and influence leaflet biocompatibility. The purpose of this study was to investigate the biocompatibility of this composite material using both small animal (nonfunctional mode) and large animal (functional mode) models. Composite samples were manufactured using dip coating and solvent casting with different coating thickness (251μm and 50μm). Sample's surface was characterized through qualitative SEM observation and quantitative surface roughness analysis. A novel rat abdominal aorta model was developed to test the composite samples in a similar pulsatile flow condition as its intended use. The sample's tissue response was characterized by histological examination. Among the samples tested, the 25μm solvent-cast sample exhibited the smoothest surface and best biocompatibility in terms of tissue capsulation thickness, and was chosen as the method for fabrication of the SIBS valve. Phosphocholine was used to create a hydrophilic surface on selected composite samples, which resulted in improved blood compatibility. Four SIBS valves (two with phosphocholine modification) were implanted into sheep. Echocardiography, blood chemistry, and system pathology were conducted to evaluate the valve's performance and biocompatibility. No adverse response was identified following implantation. The average survival time was 76 days, and one sheep with the phosphocholine modified valve passed the FDA minimum requirement of 140 days with approximately 20 million cycles of valve activity. The explanted valves were observed under the aid of a dissection microscope, and evaluated via histology, SEM and X-ray. Surface cracks and calcified tissue deposition were found on the leaflets. In conclusion, we demonstrated the applicability of using a new rat abdominal aorta model for biocompatibility assessment of polymeric materials. A smooth and complete coating surface is essential for the biocompatibility of PET/SIBS composite, and surface modification using phosphocholine improves blood compatibility. Extrinsic calcification was identified on the leaflets and was associated with regions of surface cracks.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

In vivo characterization of myocardial tissue post myocardial infarction using combined fluorescence and diffuse reflectance spectroscopy

Accurately assessing the extent of myocardial tissue injury induced by Myocardial infarction (MI) is critical to the planning and optimization of MI patient management. With this in mind, this study investigated the feasibility of using combined fluorescence and diffuse reflectance spectroscopy to characterize a myocardial infarct at the different stages of its development. An animal study was conducted using twenty male Sprague-Dawley rats with MI. In vivo fluorescence spectra at 337 nm excitation and diffuse reflectance between 400 nm and 900 nm were measured from the heart using a portable fiber-optic spectroscopic system. Spectral acquisition was performed on (1) the normal heart region; (2) the region immediately surrounding the infarct; and (3) the infarcted region—one, two, three and four weeks into MI development. The spectral data were divided into six subgroups according to the histopathological features associated with various degrees/severities of myocardial tissue injury as well as various stages of myocardial tissue remodeling, post infarction. Various data processing and analysis techniques were employed to recognize the representative spectral features corresponding to various histopathological features associated with myocardial infarction. The identified spectral features were utilized in discriminant analysis to further evaluate their effectiveness in classifying tissue injuries induced by MI. In this study, it was observed that MI induced significant alterations (p < 0.05) in the diffuse reflectance spectra, especially between 450 nm and 600 nm, from myocardial tissue within the infarcted and surrounding regions. In addition, MI induced a significant elevation in fluorescence intensities at 400 and 460 nm from the myocardial tissue from the same regions. The extent of these spectral alterations was related to the duration of the infarction. Using the spectral features identified, an effective tissue injury classification algorithm was developed which produced a satisfactory overall classification result (87.8%). The findings of this research support the concept that optical spectroscopy represents a useful tool to non-invasively determine the in vivo pathophysiological features of a myocardial infarct and its surrounding tissue, thereby providing valuable real-time feedback to surgeons during various surgical interventions for MI.

Motion correction algorithm of lung tumors for respiratory gated PET images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

A digital signal processing approach for affective sensing of a computer user through pupil diameter monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

Design of an automated book reader as an assistive technology tool for blind persons

This dissertation introduces a novel automated book reader as an assistive technology tool for persons with blindness. The literature shows extensive work in the area of optical character recognition, but the current methodologies available for the automated reading of books or bound volumes remain inadequate and are severely constrained during document scanning or image acquisition processes. The goal of the book reader design is to automate and simplify the task of reading a book while providing a user-friendly environment with a realistic but affordable system design. This design responds to the main concerns of (a) providing a method of image acquisition that maintains the integrity of the source (b) overcoming optical character recognition errors created by inherent imaging issues such as curvature effects and barrel distortion, and (c) determining a suitable method for accurate recognition of characters that yields an interface with the ability to read from any open book with a high reading accuracy nearing 98%. This research endeavor focuses in its initial aim on the development of an assistive technology tool to help persons with blindness in the reading of books and other bound volumes. But its secondary and broader aim is to also find in this design the perfect platform for the digitization process of bound documentation in line with the mission of the Open Content Alliance (OCA), a nonprofit Alliance at making reading materials available in digital form. The theoretical perspective of this research relates to the mathematical developments that are made in order to resolve both the inherent distortions due to the properties of the camera lens and the anticipated distortions of the changing page curvature as one leafs through the book. This is evidenced by the significant increase of the recognition rate of characters and a high accuracy read-out through text to speech processing. This reasonably priced interface with its high performance results and its compatibility to any computer or laptop through universal serial bus connectors extends greatly the prospects for universal accessibility to documentation.

Enhanced biocompatibility of Nitinol via surface treatment and alloying

It is projected that by 2020, there will be 138 million Americans over 45, the age at which the increased incidence of heart diseases is documented. Many will require stents. This multi-billion dollar industry, with over 2 million patients worldwide, 15% of whom use Nitinol stents have experienced a decline in sales recently, due in part to thrombosis. It is a sudden blood clot that forms inside stents. As a result, the Food and Drug Administration and American Heart Association are calling for a new generation of stents, new designs and different alloys that are more adaptable to the arteries. The future of Nitinol therefore depends on a better understanding of the mechanisms by which Nitinol surfaces can be rendered stable and inert. In this investigation, binary and ternary Nitinol alloys were prepared and subjected to various surface treatments such as electropolishing (EP), magnetoelectropolishing (MEP) and water boiling & passivation (W&P). In vitro corrosion tests were conducted on Nitinol alloys in accordance with ASTM F 2129-08. The metal ions released into the electrolyte during corrosion tests were measured by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). Biocompatibility was assessed by observing the growth of human umbilical vein endothelial cells (HUVEC) on the surface of Nitinol alloys. Static and dynamic immersion tests were performed by immersing the Nitinol alloys in cell culture media and measuring the amount of metal ions released in solution. Sulforhodamine B (SRB) assays were performed to elucidate the effect of metal ions on the growth of HUVEC cells. The surfaces of the alloys were studied using Scanning Electron Microscopy (SEM) and X-ray Photoelectron Spectroscopy (XPS) respectively. Finally, wettability and surface energy were measured by Contact Angle Meter, whereas surface roughness was measured by Atomic Force Microscopy (AFM). All the surface treated alloys exhibited high resistance to corrosion when compared with untreated alloys. SRB assays revealed that Ni and Cu ions exhibited greater toxicity than Cr, Ta and Ti ions on HUVEC cells. EP and MEP alloys possessed relatively smooth surfaces and some were composed of nickel oxides instead of elemental nickel as determined by XPS. MEP exhibited lowest surface energy and lowest surface roughness.

Principal component analysis and assessment of language network activation patterns in pediatric epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Cancer therapy combining the modalities of hyperthermia and chemotherapy: In vitro cellular response after rapid heat accumulation in the cancer cell

Hyperthermia is usually used at a sub-lethal level in cancer treatment to potentiate the effects of chemotherapy. The purpose of this study is to investigate the role of heating rate in achieving synergistic cell killing by chemotherapy and hyperthermia. For this purpose, in vitro cell culture experiments with a uterine cancer cell line (MES-SA) and its multidrug resistant (MDR) variant MES-SA/Dx5 were conducted. The cytotoxicity, mode of cell death, induction of thermal tolerance and P-gp mediated MDR following the two different modes of heating were studied. Doxorubicin (DOX) was used as the chemotherapy drug. Indocyanine green (ICG), which absorbs near infrared light at 808nm (ideal for tissue penetration), was chosen for achieving rapid rate hyperthermia. A slow rate hyperthermia was provided by a cell culture incubator. The results show that the potentiating effect of hyperthermia to chemotherapy can be maximized by increasing the rate of heating as evident by the results from the cytotoxicity assay. When delivered at the same thermal dose, a rapid increase in temperature from 37°C to 43°C caused more cell membrane damage than gradually heating the cells from 37°C to 43°C and thus allowed for more intracellular accumulation of the chemotherapeutic agents. Different modes of cell death are observed by the two hyperthermia delivery methods. The rapid rate laser-ICG hyperthermia @ 43°C caused cell necrosis whereas the slow rate incubator hyperthermia @ 43°C induced very mild apoptosis. At 43°C a positive correlation between thermal tolerance and the length of hyperthermia exposure is identified. This study shows that by increasing the rate of heating, less thermal dose is needed in order to overcome P-gp mediated MDR.

Clinical translation of a hand-held optical imager for breast cancer diagnostics: In vitro and in vivo tomography studies

Optical imaging is an emerging technology towards non-invasive breast cancer diagnostics. In recent years, portable and patient comfortable hand-held optical imagers are developed towards two-dimensional (2D) tumor detections. However, these imagers are not capable of three-dimensional (3D) tomography because they cannot register the positional information of the hand-held probe onto the imaged tissue. A hand-held optical imager has been developed in our Optical Imaging Laboratory with 3D tomography capabilities, as demonstrated from tissue phantom studies. The overall goal of my dissertation is towards the translation of our imager to the clinical setting for 3D tomographic imaging in human breast tissues. A systematic experimental approach was designed and executed as follows: (i) fast 2D imaging, (ii) coregistered imaging, and (iii) 3D tomographic imaging studies. (i) Fast 2D imaging was initially demonstrated in tissue phantoms (1% Liposyn solution) and in vitro (minced chicken breast and 1% Liposyn). A 0.45 cm3 fluorescent target at 1:0 contrast ratio was detectable up to 2.5 cm deep. Fast 2D imaging experiments performed in vivo with healthy female subjects also detected a 0.45 cm3 fluorescent target superficially placed ∼2.5 cm under the breast tissue. (ii) Coregistered imaging was automated and validated in phantoms with ∼0.19 cm error in the probe’s positional information. Coregistration also improved the target depth detection to 3.5 cm, from multi-location imaging approach. Coregistered imaging was further validated in-vivo , although the error in probe’s positional information increased to ∼0.9 cm (subject to soft tissue deformation and movement). (iii) Three-dimensional tomography studies were successfully demonstrated in vitro using 0.45 cm3 fluorescence targets. The feasibility of 3D tomography was demonstrated for the first time in breast tissues using the hand-held optical imager, wherein a 0.45 cm3 fluorescent target (superficially placed) was recovered along with artifacts. Diffuse optical imaging studies were performed in two breast cancer patients with invasive ductal carcinoma. The images showed greater absorption at the tumor cites (as observed from x-ray mammography, ultrasound, and/or MRI). In summary, my dissertation demonstrated the potential of a hand-held optical imager towards 2D breast tumor detection and 3D breast tomography, holding a promise for extensive clinical translational efforts.

Automated detection of hematological abnormalities through classification of flow cytometric data patterns

Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

Development of micro immunosensors to study genomic and proteomic biomarkers related to cancer and Alzheimer's disease

A report from the National Institutes of Health defines a disease biomarker as a “characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer’s disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with biorecognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0–100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Aβ) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Aβ1-40/42 (or Aβ ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Aβ1-40 and Aβ1-42 in cerebrospinal fluid from rats within a detection range of 100nM to 1.2μM and 400nM to 1μM respectively. In addition, the release of DNA damage/repair biomarker 8-hydroxydeoxyguanine (8-OHdG) under the influence of reactive oxidative stress from single lung endothelial cell was monitored using an activated carbon fiber microelectrode. The sensor was used to test the influence of nicotine, which is one of the most biologically active chemicals present in cigarette smoke and smokeless tobacco.

Electro and Magneto-Electropolished Surface Micro-Patterning on Binary and Ternary Nitinol

In this study, an Atomic Force Microscopy (AFM) roughness analysis was performed on non-commercial Nitinol alloys with Electropolished (EP) and Magneto-Electropolished (MEP) surface treatments and commercially available stents by measuring Root-Mean-Square (RMS) , Average Roughness (Ra), and Surface Area (SA) values at various dimensional areas on the alloy surfaces, ranging from (800 x 800 nm) to (115 x 115µm), and (800 x 800 nm) to (40 x 40 µm) on the commercial stents. Results showed that NiTi-Ta 10 wt% with an EP surface treatment yielded the highest overall roughness, while the NiTi-Cu 10 wt% alloy had the lowest roughness when analyzed over (115 x 115 µm). Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) analysis revealed unique surface morphologies for surface treated alloys, as well as an aggregation of ternary elements Cr and Cu at grain boundaries in MEP and EP surface treated alloys, and non-surface treated alloys. Such surface micro-patterning on ternary Nitinol alloys could increase cellular adhesion and accelerate surface endothelialization of endovascular stents, thus reducing the likelihood of in-stent restenosis and provide insight into hemodynamic flow regimes and the corrosion behavior of an implantable device influenced from such surface micro-patterns.